Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks
Vehicle information extraction is the key means in Intelligent Transportation System (ITS). Color plays an important role in vehicle recognition. The main challenge of vehicle color recognition is to find the dominant color. In this paper, we propose a color recognition method using convolutional neural network. We train the classifier with the network structure NIN to increase the classification accuracy. The experiments are validated on our dataset and extra data, which are collected from city surveillance equipment. The proposed method outperforms other competing color recognition methods.
Vehicle Color Recognition Deep Convolutional Nerual Networks network in network
Boyang Su Jie Shao Jianying Zhou Xiaoteng Zhang Lin Mei
Internet of things technology department The Third Research Institute of the Ministry of Public Security Shanghai, P.R. China
国际会议
重庆
英文
790-793
2015-12-18（万方平台首次上网日期，不代表论文的发表时间）